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Skyvern

What it is

Skyvern is an open-source browser automation platform that uses LLMs and Computer Vision to automate complex workflows on any website.

What problem it solves

It replaces brittle, DOM-based automation (like traditional Playwright or Selenium scripts) with a visual-reasoning approach that "sees" the page, making it resistant to layout changes.

Where it fits in the stack

Infrastructure / Framework. It provides a high-level, visual-reasoning-driven layer for browser-based agents.

Typical use cases

  • Multi-Site Workflows: Applying the same task (e.g., "download invoice") across dozens of different sites.
  • Visual Validation: Checking UI elements and workflows based on visual appearance.
  • Workflow Automation: Replacing unreliable DOM-parsing scripts.

Strengths

  • Resilient: Vision-based reasoning doesn't break when CSS classes or XPaths change.
  • No-Code / Low-Code: Includes a workflow builder for non-technical users.
  • Playwright Compatible: Can be integrated into existing Playwright-based SDKs.
  • High Stars: Popular project with 20k+ stars.

Limitations

  • Vision Model Costs: Requires high-quality vision models, which are slower and more expensive.
  • Inference Latency: Visual reasoning takes time, making it unsuitable for real-time applications.
  • Resource Intensive: Requires significant compute (GPU) for local vision processing.

When to use it

  • When you need to automate workflows across many different websites.
  • For tasks where DOM parsing is extremely difficult or unreliable.

When not to use it

  • For high-speed, simple data extraction from single-site APIs.
  • When budget or latency constraints are strict.

Getting started

Installation

Skyvern is typically deployed via Docker for local use or accessed via the Skyvern Cloud.

git clone https://github.com/Skyvern-AI/skyvern.git
cd skyvern
docker-compose up

Basic Usage

Once the Docker containers are running, you can access the Skyvern UI at http://localhost:8000 to create your first automation workflow.

CLI examples

# Start the Skyvern server and worker using Docker
docker-compose up -d

# Check the status of the Skyvern worker
docker-compose ps worker

# View logs from the Skyvern API server
docker-compose logs -f api

API examples

import requests

# Trigger a Skyvern workflow via the API
response = requests.post(
    "http://localhost:8000/api/v1/workflows/execute",
    json={
        "url": "https://example.com/login",
        "navigation_goal": "Log in and navigate to the invoices page",
        "extraction_goal": "Extract the last 3 invoice numbers and amounts"
    },
    headers={"Authorization": "Bearer YOUR_API_KEY"}
)

print(response.json())

Licensing and cost

  • Open Source: Yes (MIT)
  • Cost: Free (Self-hosted) / Paid (Skyvern Cloud)
  • Self-hostable: Yes

Sources / References

Contribution Metadata

  • Last reviewed: 2026-05-22
  • Confidence: high